A vast diversity of individual tumor cells exists in every patient with cancer. Those cells display distinct behaviors related to cancer growth, metastasis and responses to chemotherapy. To carry out these behaviors, each cancer cell uses its genes to construct the needed molecules in a unique way known as its "gene expression signature."
To correlate gene expression signatures with cancer progression and chemotherapy resistance, a team of scientists led by Akil A. Merchant, MD, a Cedars-Sinai Cancer hematology researcher, and Rong Lu, PhD, an assistant professor of Stem Cell & Regenerative Medicine at the University of Southern California, have introduced a new genetic technology in a study of laboratory mice, published recently in Nature Communications.
To develop the system, the researchers combined two existing technologies. The first enabled the researchers to read the gene expression signatures of individual cancer cells from patients with leukemia. The second allowed the scientists to label individual leukemia cells with heritable, DNA-based "barcodes," offering a way to track not only the cells but also their progeny during disease progression.
"We were able to identify previously unknown genes that are involved in disease progression and chemotherapy resistance," said Merchant, director of the Imaging Mass Cytometry Core at Cedars-Sinai Cancer and an associate professor of Medicine. "These genes may provide new targets for future therapies."
Using this experimental system, the team analyzed the gene expression signatures of a representative sample of barcoded leukemia cells, and then transplanted the remainder of the cells into mice.
Distinct gene expression signatures correlated with the various organs where the cancer cells ended up in the mice. For example, cancer cells with a high expression of one type of gene tended to colonize the ovaries, while cells with low levels of a different gene expression established colonies in the blood and spleen.
By demonstrating that cancer cells with distinct gene expression signatures tend to grow in different organs and bone marrow pockets, the study also underscored a major problem facing cancer researchers: studying non-representative samples of patient cells. For instance, if a physician collects patient cells via a standard blood draw, that sample would not include the non-circulating leukemia cells localized to pockets of the bone marrow. Even more concerning, since these pockets of cancer cells are not uniformly distributed, standard bone marrow biopsies may not accurately diagnose disease in the patient.
There are similar challenges when patient cells are transplanted into laboratory mice in order to conduct pre-clinical cancer research. Less than 1% of patient cells grow and multiply in mice.
These problems are compounded if patient cells are collected from one mouse and then transplanted into another. The new findings demonstrate that serial transplantations also favor the survival of cancer cells with certain gene expression signatures.
"Our new system laid bare glaring limitations in the leukemia models that are currently used to carry out the final stages of testing before potential therapeutic treatments advance to human clinical trials," Lu said. "These leukemia models do not capture the full diversity of individual tumor cells within a single patient, let alone within the broader population of patients affected by this disease."
The researchers also tested variations of the standard leukemia treatment regimen: short-term intensive chemotherapy, followed by long-term maintenance therapy. Distinct gene expression signatures emerged in leukemia cells that eventually died from intensive treatment, and ceased growing due to maintenance therapy. In some instances, they responded only to a combination of both. Accordingly, in actual clinical practice, combination therapy has proven to be the best overall approach for patients.
"By using our experimental system, we learned a lot about how the gene expression of individual leukemia cells influence their progression and treatment resistance," Merchant said. "The same system can provide similar insights about many other types of cancer and help identify and characterize the particular cells that drive the disease and underlie treatment resistance."
Research reported in this study was supported by federal funding from the National Heart, Lung, and Blood Institute (grants R35HL150826, R01HL138225, and R01HL135292); the National Cancer Institute (grants R35CA197628, R01CA213138, R01CA157644, P01CA233412, F31CA206463, and P30CA014089); the California Institute for Regenerative Medicine (EDUC2-08381); the Howard Hughes Medical Institute (HHMI-55108547; the University of Southern California Provost’s Undergraduate Research Fellowship, and the Rose Hills Research Fellowship.